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The recent development of high-resolution omics level technologies has reshaped modern biological research. These high-dimensional and noisy datasets are accumulating at a fast pace. Efficient and biologically meaningful algorithms are needed to extract biological insights from these raw datasets. In this talk, I will discuss using optimal transport, a powerful geometric data analysis method, to integrate multimodal omics datasets and to infer cell-cell communications, a crucial process that drives the correct developments and functions of biological systems. I will also talk about a formulation of optimal transport called supervised optimal transport inspired by these biological applications. |